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Abstract

Introduction

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease. Cardiovascular
disease (CVD) is common and a major cause of mortality. Studies on cardiovascular
morbidity are abundant, whereas mortality studies focusing on cardiovascular outcomes
are scarce. The aim of this study was to investigate causes of death and baseline
predictors of overall (OM), non-vascular (N-VM), and specifically cardiovascular (CVM)
mortality in SLE, and to evaluate systematic coronary risk evaluation (SCORE).

Methods

208 SLE patients were included 1995-1999 and followed up after 12 years. Clinical
evaluation, CVD risk factors, and biomarkers were recorded at inclusion. Death certificates
and autopsy protocols were collected. Causes of death were divided into CVM (ischemic
vascular and general atherosclerotic diseases), N-VM and death due to pulmonary hypertension.
Predictors of mortality were investigated using multivariable Cox regression. SCORE
and standardized mortality ratio (SMR) were calculated.

Results

During follow-up 42 patients died at mean age of 62 years. SMR 2.4 (CI 1.7-3.0). 48%
of deaths were caused by CVM. SCORE underestimated CVM but not to a significant level.
Age, high cystatin C levels and established arterial disease were the strongest predictors
for all- cause mortality. After adjusting for these in multivariable analyses, only
smoking among traditional risk factors, and high soluble vascular cell adhesion molecule-1
(sVCAM-1), high sensitivity C-reactive protein (hsCRP), anti-beta2 glycoprotein-1
(abeta2GP1) and any antiphospholipid antibody (aPL) among biomarkers, remained predictive
of CVM.

Conclusion

With the exception of smoking, traditional risk factors do not capture the main underlying
risk factors for CVM in SLE. Rather, cystatin C levels, inflammatory and endothelial
markers, and antiphospholipid antibodies (aPL) differentiate patients with favorable
versus severe cardiovascular prognosis. Our results suggest that these new biomarkers
are useful in evaluating the future risk of cardiovascular mortality in SLE patients.

Cardiovascular disease (CVD) is a well studied co-morbidity of SLE with many remaining
questions to be answered. Both subclinical CVD, measured as atherosclerosis, and clinical
events have been subjects for investigation. Studies have focused on different aspects
of the disease to find associations with, and to characterize, SLE-related CVD. For
example, CVD in SLE has been associated with clinical manifestations, disease activity
and damage, traditional and non-traditional riskfactors, and demographic factors [1-4]. Risk factors for cardiovascular mortality (CVM) in SLE on the other hand, have not yet been well studied.

In the 1950s, the estimated 5-year survival was less than 50% [5], but recent studies report 5-year survival of over 90% [6,7]. Nevertheless, the mortality rate in SLE still exceeds that of the general population
[8,9]. Death related to lupus activity and infection has decreased over time, but still
contributes to mortality [10,11], especially in developing countries[12,13]. However, CVM has not declined [14] in SLE. A slight increased standardized mortality ratio (SMR) due to vascular diseases
has been reported [15], and death from CVD accounts for between 17% and 76% in different studies [16,17]. To date, most studies have investigated risk factors for overall mortality (OM),
sometimes with diverging results [10,12,18-21]. As CVM accounts for a growing part of mortality in SLE, it is important to identify
risk factors specifically for CVM. In the general population, the systematic coronary
risk evaluation (SCORE) [22] is a well-established tool to predict the 10-year risk of CVM based on traditional
risk factors. SCORE has not previously been evaluated in SLE. Many new biomarkers
that could help identify underlying molecular pathways of importance for vascular
damage, such as endothelial and inflammatory markers and cystatin C have not been
evaluated with respect to mortality in SLE.

Therefore, we described a large set of biomarkers and SCORE in a cohort of 208 SLE
patients from a single center. We determined causes of death and the contribution
of baseline predictors for OM, CVM and non-vascular mortality (N-VM).

Materials and methods

During the inclusion period (1995 to 1998), 208 patients with prevalent disease, who
were attending the Department of Rheumatology, Karolinska University Hospital, and
fulfilled four or more of the 1982 revised American College of Rheumatology criteria
for classification of SLE [23] were included. Most patients (94%) were European Caucasians. The Local Ethics Committee
at Karolinska University Hospital approved the study and patients provided informed
consent.

At inclusion, all data were collected in one session for each patient. A rheumatologist
interviewed and examined patients according to a structured protocol. Medical history,
traditional CVD risk factors (smoking, hypertension, hypercholesterolemia, diabetes)
and medication were reviewed, through interviewing the patient and by studying medical
records. SLE disease activity was determined using the Systemic Lupus Activity Measure
(SLAM) [24] and organ damage was assessed using the Systemic Lupus International Collaborating
Clinics (SLICC) damage index [25]. Laboratory examinations were performed on fasting fresh blood samples or on samples
stored at -70°C. When stored samples were used, each analyte was assayed in one session.

Survival status was followed up in the national population registry on March 26, 2010,
after a mean time of 12.3 years. Two patients were interviewed by telephone as they
had moved abroad. Death certificates were collected from the Cause of Death Register
of The National Board of Health and Welfare. When available, autopsy protocols were
collected from the department of Pathology, Karolinska University Hospital (n = 10),
and from the Department of Forensic Medicine (n = 4). Causes of death were based on
information from death certificates, autopsy protocols and medical records. Two clinicians
(JG and ES) classified all causes of death together as follows: CVM (death due to
myocardial infarction, atherosclerosis, heart failure, ischemic cerebrovascular disease
or sudden death), death due to pulmonary hypertension (PHT) and N-VM.

Statistics

Patient characteristics were summarized overall and stratified by outcome using analysis
of variance (ANOVA), Mann-Whitney U-test and Chi2 test, as appropriate. Skewed continuous variables were log transformed before use
in parametric analyses. The SMR for all deaths and corresponding 95% confidence interval
(CI) assuming a Poisson distribution was calculated using age-, sex-, and calendar
year-specific mortality rates for the Swedish population to estimate the expected
number of deaths. Hazard ratios (HRs), it should be hazard ratios everywhere and 95%
CI for OM, CVM and N-VM were calculated in age-adjusted Cox models for baseline factors.
The proportional hazards assumption was evaluated by assessing the significance of
the interaction between predictors and follow-up time and the assumption was met.
PHT was included in OM but otherwise excluded because of too few cases. The limited
number of deaths restricted the variables in the multivariable-adjusted model to four.
The two predictors most strongly associated with mortality after age adjustment (in
terms of P-value) in the three groups (OM, CVM, N-VM) were retained in all multivariable analyses.
Thereafter, each baseline variable was considered separately in multivariable models.

To evaluate the different multivariable models predicting CVM in terms of identifying
the best model, and to compare that model with SCORE, Akaike information criterion
(AIC) values were compared using logistic regression. To consider the possibility
of effect modification by sex, we stratified by sex; we restricted the sensitivity
analysis to the female subset. Male patients were not considered due to small sample
size. Possible effect modification on cystatin C by steroid treatment was evaluated
by stratifying by steroid treatment. To account for the possibility that subclinical
or unregistered nephritis could affect the cystatin C results, we also stratified
by history of nephritis.

SCORE [22] was calculated using the Swedish Heartscore. Baseline data on age, smoking, sex,
systolic blood pressure and cholesterol were incorporated into the web-based formula
[27]. The 10-year risk of CVM was calculated for patients between 40 to 65 years of age,
according to the SCORE protocol. The estimated number of CVMs was compared to the
observed number using Fisher´s exact analysis.

Multiple imputation was used for missing data. For dichotomous variables the models
were re-run assuming each possible value and the results were compared. For continuous
predictors, three imputed values were used: the minimum, the mean, and the maximum
value. Descriptive statistics and regression analyses were done using JMP software
(SAS Institute, Carey, North Carolina, USA) and SAS 9.2 was used for SMR calculations.
A P-value ≤ 0.05 was considered statistically significant.

Results

All patients were followed up. Forty-two patients (20%) died, 36 women and 6 men,
at a mean age of 62 years (women 61 ± SD 14, men 64 ± 19 years). More deaths were
observed than expected (SMR = 2.4, 95% CI 1.7 to 3.0). CVM was the predominant cause
of death (n = 20, 48%) (Table 1).

At inclusion, 124 patients were between 40 and 65 years of age. In this group, we
observed nine cardiovascular deaths within 10 years. SCORE only predicted four deaths
and the difference was not statistically significant (odds ratio, OR 2.3, 95% CI 0.7
to 7.8, P = 0.25).

Several parameters measured at baseline differed between deceased and surviving patients
(Table 2) and persisted after age adjustment for all outcomes. Established arterial disease
and Cystatin C were the strongest risk factors in all groups (Table 3) and were retained in the remaining analyses (Table 4). OM was predicted by several inflammatory parameters, sVCAM-1 and SLICC >1.

Smoking was the only traditional risk factor predicting CVM. sVCAM-1, hsCRP, aβ2GP1, any aPL at medium titer, and baseline warfarin treatment also predicted CVM.
N-VM was positively associated with markers of systemic inflammation and SLICC >1,
while SSB autoantibodies were inversely associated (Table 4). Results were similar among women, with a few exceptions (see Table 5). The best multivariable model predicting CVM included age, established arterial
disease, cystatin C and smoking (AICc value 77). Yes, the same thing All six multivariable
models predicting CVM (AICc values ranging from 77 to 85) performed better than SCORE
(AICc value 122).

Stratification by steroid treatment did not influence the impact of cystatin C on
mortality. Among those without history of nephritis (n = 135 of whom 25 died cystatin
C adjusted for age remained significant; P = 0.009, RR 4.6 (95% CI 1.5 to 14.5). For patients with history of nephritis (n =
73 of whom 17 died), the results for cystatin C were similar; P = 0.001, RR 4.4 (95% CI 1.8 to 10.7).

Results were comparable under the numerous imputed scenarios with the exception of
cyclophosphamide, where a large proportion of missingness was observed among deceased
patients, and alternative imputed scenarios yielded different results. As these were
considered unreliable, they were removed from consideration.

Discussion

To our knowledge, this is the first study to prospectively examine risk factors specifically
for CVM, which accounted for almost 50% of deaths in our cohort. Additionally, 10%
of patients died from PHT. CVM and N-VM shared many risk factors. Established arterial
disease, Cystatin C and inflammatory markers were strong predictors for both, but
s-VCAM-1, a marker of endothelial cell activation, was only associated with CVM. Also,
aβ2GP1 and any aPL at medium titer predicted CVM. SCORE underestimated the risk for CVM,
but the results were not statistically significant. Consistent with recently published
work [9,15], SMR was 2.4. Our survival rate of 80% after a mean follow-up of approximately 12
years is generally consistent with previous findings, which range from 76% to 92%
survival after 10 years [28,29]. Our results confirm [6,17,30] that composite damage (SLICC > 1[25]) predicted OM, but our focus was to analyze the impact of different organ manifestations
and immunological profile on mortality.

High levels of cystatin C and low estimated glomerular filtration rate (eGFR) based
on cystatin C [31] emerged as strong predictors for all outcomes. These associations were independent
of inflammatory and endothelial biomarkers and were not modified by steroid treatment
at baseline. Creatinine and eGRF, calculated using the Modification of Diet in Renal
Disease (MDRD) formula [32] did not predict mortality.

Renal disease in lupus is associated with poor prognosis [10,20,33]. Cystatin C has been proposed as a more reliable biomarker for renal function than
creatinine as it rises with smaller reductions in GFR [34], and is less influenced by age, sex, muscle mass and diet [35]. Nevertheless, cystatin C levels may be affected by glucocorticoid use [36] and inflammation [37], both often present in SLE. Cystatin C has furthermore emerged as a marker of CVD
risk [38], CVM and N-VM in subjects with normal eGFR [39]. The fact that the nephritis manifestation in our study only influenced CVM to a
modest degree, while cystatin C predicted mortality significantly both in patients
with and without reported history of nephritis, further emphasizes the importance
of cystatin C as a new useful biomarker. Our results demonstrate that cystatin C is
strongly predictive of mortality and that it merits further evaluation as a biomarker
in SLE.

sVCAM-1 was a strong risk factor for OM and in particular for CVM, underscoring the
importance of endothelial activation for CVM in lupus. Endothelial biomarkers have
not previously been investigated in the context of mortality in SLE. Levels of sVCAM-1
are elevated in SLE patients with manifest CVD [40] and together with vWf, another endothelial marker, they predicted the first arterial
event [26]. An association with atherosclerosis has been demonstrated both in the general population
and in lupus [4].

Systemic inflammation is associated with CVD, CVM and N-VM in the general population
[41,42] and may be associated with CVD in lupus [26,43-45], although the impact on mortality has not yet been well studied. We demonstrated
that several inflammatory markers were associated with all-cause mortality. For CVM,
hsCRP (and α1-antitrypsin among women) had the greatest impact.

aβ2GP1 and any aPL at medium titer were associated with CVM in multivariable analyses.
This observation is in accordance with previous studies, where aPLs were associated
with cardiovascular events [26,44]. The high prevalence of aCL in our study is probably due to a low cutoff for positivity
at our laboratory in the mid 90's, when baseline data were collected. Since then,
much work has been carried out to evaluate more appropriate cutoffs for aCL in relation
to what is clinically significant [46]. When we used a cutoff at medium titer, the prevalence of aCL was more in accordance
with other studies [47]. Furthermore, medium titer of aPLs were predictive of CVM, indicating that these
are more clinically relevant levels. However, we have previously demonstrated that
aPL only at a low cutoff were predictive of the first arterial event [26]. aβ2GP1 was analyzed later on frozen samples, with the method currently used at our immunological
laboratory. Taken together, our results demonstrate that clinically relevant levels
for aPL need to be further studied and standardized. Studies in our research group
are ongoing to investigate these issues.

SSA/SSB antibodies often occur together with skin manifestations in SLE. We noted
an inverse association between positivity for SSB antibodies and N-VM. SSA antibodies
[20] and photosensitivity [10] were previously inversely linked to mortality. Together these results indicate that
lupus patients with SSA/SSB positivity and/or skin manifestations have a better prognosis,
further illustrating that sub-phenotypes of SLE have differentiated risk profiles
[26].

Smoking was the only traditional CVD risk factor associated with CVM in multivariable
analyses. Smoking has previously been shown to predict cardiovascular events in SLE
[26,44]. Hypertension was predictive of mortality in earlier SLE studies [19,48]. As definitions differ and antihypertensive agents are used in the treatment of nephritis,
even in the absence of high blood pressure, it is nowadays difficult to assess its
contribution to mortality. Hyperlipidemia was not an important risk factor for mortality
in multivariable analyses.

SCORE is a widespread clinical cardiovascular risk scoring system distributed through
the European Society of Cardiology. SCORE underestimated CVM among our SLE patients
(nine observed vs. four predicted cases), but the difference was not significant.
This is nevertheless interesting as it suggests that optimal preventive cardiovascular
strategies in lupus need to target other factors in addition to traditional CVD risk
factors.

Notably, four SLE patients (10%) in this cohort died from PHT. They died at a young
mean age (41 years). Death from PHT was 15% in a Korean cohort [49], but in most studies PHT is not reported as a prominent cause of death.

Detailed baseline information and complete follow-up are strengths of this study.
Assigning a principle cause of death is difficult, particularly in patients with chronic
diseases with numerous co-morbidities. We did not rely on death certificates only,
but supplemented these data with autopsy protocols and medical charts, thus using
all available sources to determine a main cause of death. Because national mortality
data are based solely on international classification of diseases (ICD) codes, derived
from only one of the data sources we considered in the determination of cause of death,
cause-specific SMRs could not be calculated. It is difficult to compare causes of
death in our cohort and in the general population for the same reason.

The majority of our patients were female, and of European Caucasian origin. Because
Swedish healthcare is tax-funded, granting universal access, patients with lower socioeconomic
status have the same access with the same threshold maximum payment per year. Therefore
further studies in male patients, other ethnic cohorts and socioeconomic groups are
needed. Furthermore, we had limited statistical power. For example, only 13 deaths
occurred among patients aged 50 years or younger, prohibiting the evaluation of effect
modification by age. Another limitation of this study is the assessment of risk factors
at baseline only, which makes it difficult to evaluate development of disease manifestations
and other events during follow-up. Finally, we did not adjust for multiple comparisons,
and therefore P-values close to 0.05 should be interpreted with caution.

Conclusions

This study demonstrates that high levels of cystatin C strongly predicted all cause
mortality. Additionally, CVM was associated with high levels of sVCAM-1, hsCRP and
aPL, demonstrating that systemic and vascular inflammation, and prothrombotic autoantibodies
are important risk factors for CVM. With the exception of smoking, traditional risk
factors had less impact. Thus, new biomarkers differentiate SLE patients with favorable
vs. more severe prognosis.

Competing interests

The authors declare that they have no competing interests.

Authors' contributions

JG acquired, analyzed and interpreted the data and drafted the manuscript. JFS analyzed
the data and drafted the manuscript. KE coordinated and acquired the analysis of autoantibodies.
IEL acquired the data. LOH and AL coordinated and acquired the laboratory data. ES
conceived and designed the study, acquired, analyzed and interpreted the data and
drafted the manuscript. All authors reviewed and approved the final manuscript.

Acknowledgements

We are grateful to Jill Gustafsson, Sonia Möller, Susanne Pettersson and Eva Jemseby
for management of patient cohorts and blood sampling. This work was supported by the
Swedish Heart-Lung Foundation, Stockholm County Council and Karolinska Institutet
(ALF), The King Gustaf V 80th Birthday Fund, The Swedish Rheumatism Association, The
Åke Wiberg Foundation, Alex and Eva Wallströms Foundation, Karolinska Institutet´s
Foundations, and The Foundation in memory of Clas Groschinsky, The Swedish Society
of Medicine.